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Summary

This catalog of design patterns for agentic AI applications is organized into nine categories, each addressing different aspects of intelligent agent design and implementation. These categories represent the major architectural and behavioral concerns that arise when developing systems that can reason, plan, and act autonomously.

Each pattern within the categories listed below is documented using a consistent format that captures its intent, structure, implementation details, and relationship to other patterns. By organizing the patterns in this way, we aim to provide a comprehensive resource that practitioners can navigate based on the specific challenges they're addressing in their agentic AI applications.

Categories

Core Processing Patterns

Fundamental patterns that govern how agents process information, reason through problems, and generate responses. These patterns form the cognitive foundation of agentic systems.

Architectural Patterns

Structural patterns that define the organization of agent components, their relationships, and how they work together to form coherent systems.

Efficiency Patterns

Optimization techniques that improve performance, reduce costs, and make agentic systems more scalable and responsive.

Memory Management Patterns

Approaches for storing, retrieving, and utilizing information across different time scales, enabling agents to learn from experience and maintain context.

Safety Patterns

Defensive mechanisms and guardrails that help ensure agentic systems operate within appropriate boundaries and handle edge cases safely.

Human Collaboration Patterns

Interaction models that facilitate effective cooperation between human users and AI agents, balancing autonomy with appropriate human oversight.

Orchestration Patterns

Coordination techniques for managing complex workflows, multiple agents, and extended processes that span time and system boundaries.

Explainability Patterns

Methods for making agent reasoning and decision-making transparent, interpretable, and accountable to users and stakeholders.

Resilience Patterns

Approaches for building robust systems that can gracefully handle failures, adapt to changing conditions, and maintain reliability under stress.